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DeepFool: a simple and accurate method to fool deep neural networks

14 November 2015

Seyed-Mohsen Moosavi-Dezfooli

Papers citing "DeepFool: a simple and accurate method to fool deep neural networks"

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Title
PhysGAN: Generating Physical-World-Resilient Adversarial Examples for Autonomous Driving Zelun Kong Junfeng Guo Ang Li Cong Liu AAML 105 130 0 09 Jul 2019
Affine Disentangled GAN for Interpretable and Robust AV Perception Letao Liu Martin Saerbeck Justin Dauwels 35 1 0 06 Jul 2019
Adversarial Attacks in Sound Event Classification Vinod Subramanian Emmanouil Benetos N. Xu SKoT McDonald Mark Sandler AAML 36 8 0 04 Jul 2019
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack Francesco Croce Matthias Hein AAML 146 493 0 03 Jul 2019
Robust Synthesis of Adversarial Visual Examples Using a Deep Image Prior Thomas Gittings Steve A. Schneider John Collomosse AAML 61 10 0 03 Jul 2019
Treant: Training Evasion-Aware Decision Trees Stefano Calzavara Claudio Lucchese Gabriele Tolomei S. Abebe S. Orlando AAML 75 41 0 02 Jul 2019
Diminishing the Effect of Adversarial Perturbations via Refining Feature Representation Nader Asadi Amirm. Sarfi Mehrdad Hosseinzadeh Sahba Tahsini M. Eftekhari AAML 32 2 0 01 Jul 2019
Accurate, reliable and fast robustness evaluation Wieland Brendel Jonas Rauber Matthias Kümmerer Ivan Ustyuzhaninov Matthias Bethge AAML OOD 97 113 0 01 Jul 2019
Fooling a Real Car with Adversarial Traffic Signs N. Morgulis Alexander Kreines Shachar Mendelowitz Yuval Weisglass AAML 89 93 0 30 Jun 2019
Adversarial Robustness via Label-Smoothing Morgane Goibert Elvis Dohmatob AAML 124 18 0 27 Jun 2019
Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness Fanny Yang Zuowen Wang C. Heinze-Deml 126 42 0 26 Jun 2019
Defending Adversarial Attacks by Correcting logits Yifeng Li Lingxi Xie Ya Zhang Rui Zhang Yanfeng Wang Qi Tian AAML 41 5 0 26 Jun 2019
Defending Against Adversarial Examples with K-Nearest Neighbor Chawin Sitawarin David Wagner AAML 91 29 0 23 Jun 2019
Hiding Faces in Plain Sight: Disrupting AI Face Synthesis with Adversarial Perturbations Yuezun Li Xin Yang Baoyuan Wu Siwei Lyu AAML PICV CVBM 95 38 0 21 Jun 2019
Evolution Attack On Neural Networks Yigui Luo Ruijia Yang Wei Sha Weiyi Ding YouTeng Sun Yisi Wang AAML 24 0 0 21 Jun 2019
Machine Learning Testing: Survey, Landscapes and Horizons Jie M. Zhang Mark Harman Lei Ma Yang Liu VLM AILaw 110 756 0 19 Jun 2019
Cloud-based Image Classification Service Is Not Robust To Simple Transformations: A Forgotten Battlefield Dou Goodman Tao Wei AAML 69 6 0 19 Jun 2019
SemanticAdv: Generating Adversarial Examples via Attribute-conditional Image Editing Haonan Qiu Chaowei Xiao Lei Yang Xinchen Yan Honglak Lee Yue Liu AAML 69 172 0 19 Jun 2019
Adversarial attacks on Copyright Detection Systems Parsa Saadatpanah Ali Shafahi Tom Goldstein AAML 57 33 0 17 Jun 2019
Defending Against Adversarial Attacks Using Random Forests Yifan Ding Liqiang Wang Huan Zhang Jinfeng Yi Deliang Fan Boqing Gong AAML 64 14 0 16 Jun 2019
$Adversarial Robustness Assessment: Why both $L_0$ and $L_\infty$ Attacks Are Necessary$ Adversarial Robustness Assessment: Why both $L_0$ and $L_\infty$ Attacks Are Necessary Shashank Kotyan Danilo Vasconcellos Vargas AAML 34 8 0 14 Jun 2019
A Computationally Efficient Method for Defending Adversarial Deep Learning Attacks R. Sahay Rehana Mahfuz Aly El Gamal AAML 33 5 0 13 Jun 2019
Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks Ziang Yan Yiwen Guo Changshui Zhang AAML 79 111 0 11 Jun 2019
E-LPIPS: Robust Perceptual Image Similarity via Random Transformation Ensembles M. Kettunen Erik Härkönen J. Lehtinen AAML 65 63 0 10 Jun 2019
Attacking Graph Convolutional Networks via Rewiring Yao Ma Suhang Wang Tyler Derr Lingfei Wu Jiliang Tang AAML GNN 64 84 0 10 Jun 2019
On the Vulnerability of Capsule Networks to Adversarial Attacks Félix D. P. Michels Tobias Uelwer Eric Upschulte Stefan Harmeling AAML 77 24 0 09 Jun 2019
Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang Tianyun Zhang Sijia Liu Pin-Yu Chen Jiacen Xu M. Fardad Yangqiu Song AAML 83 37 0 09 Jun 2019
Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks Maksym Andriushchenko Matthias Hein 84 62 0 08 Jun 2019
ML-LOO: Detecting Adversarial Examples with Feature Attribution Puyudi Yang Jianbo Chen Cho-Jui Hsieh Jane-ling Wang Michael I. Jordan AAML 93 101 0 08 Jun 2019
Sensitivity of Deep Convolutional Networks to Gabor Noise Kenneth T. Co Luis Muñoz-González Emil C. Lupu AAML 28 6 0 08 Jun 2019
Inductive Bias of Gradient Descent based Adversarial Training on Separable Data Yan Li Ethan X. Fang Huan Xu T. Zhao 92 16 0 07 Jun 2019
Robust Attacks against Multiple Classifiers Juan C. Perdomo Yaron Singer AAML 56 11 0 06 Jun 2019
Understanding Adversarial Behavior of DNNs by Disentangling Non-Robust and Robust Components in Performance Metric Yujun Shi B. Liao Guangyong Chen Yun-Hai Liu Ming-Ming Cheng Jiashi Feng AAML 20 2 0 06 Jun 2019
Robust Neural Machine Translation with Doubly Adversarial Inputs Yong Cheng Lu Jiang Wolfgang Macherey AAML 74 255 0 06 Jun 2019
Should Adversarial Attacks Use Pixel p-Norm? Ayon Sen Xiaojin Zhu Liam Marshall Robert D. Nowak 51 21 0 06 Jun 2019
Query-efficient Meta Attack to Deep Neural Networks Jiawei Du Hu Zhang Qiufeng Wang Yi Yang Jiashi Feng AAML 66 84 0 06 Jun 2019
Enhancing Gradient-based Attacks with Symbolic Intervals Shiqi Wang Yizheng Chen Ahmed Abdou Suman Jana AAML 58 15 0 05 Jun 2019
Adversarial Training is a Form of Data-dependent Operator Norm Regularization Kevin Roth Yannic Kilcher Thomas Hofmann 58 13 0 04 Jun 2019
What do AI algorithms actually learn? - On false structures in deep learning L. Thesing Vegard Antun A. Hansen 38 21 0 04 Jun 2019
Interpretable Neural Network Decoupling Yuchao Li Rongrong Ji Shaohui Lin Baochang Zhang Chenqian Yan Yongjian Wu Feiyue Huang Ling Shao 54 2 0 04 Jun 2019
Architecture Selection via the Trade-off Between Accuracy and Robustness Zhun Deng Cynthia Dwork Jialiang Wang Yao-Min Zhao AAML 98 3 0 04 Jun 2019
Adversarially Robust Generalization Just Requires More Unlabeled Data Runtian Zhai Tianle Cai Di He Chen Dan Kun He John E. Hopcroft Liwei Wang 98 158 0 03 Jun 2019
Enhancing Transformation-based Defenses using a Distribution Classifier C. Kou H. Lee E. Chang Teck Khim Ng 67 3 0 01 Jun 2019
Perceptual Evaluation of Adversarial Attacks for CNN-based Image Classification Sid Ahmed Fezza Yassine Bakhti W. Hamidouche Olivier Déforges AAML 57 32 0 01 Jun 2019
Real-Time Adversarial Attacks Yuan Gong Boyang Li C. Poellabauer Yiyu Shi AAML 60 55 0 31 May 2019
A Review of Deep Learning with Special Emphasis on Architectures, Applications and Recent Trends Saptarshi Sengupta Sanchita Basak P. Saikia Sayak Paul Vasilios Tsalavoutis Frederick Ditliac Atiah V. Ravi R. Peters AI4CE 169 347 0 30 May 2019
Bandlimiting Neural Networks Against Adversarial Attacks Yuping Lin A. KasraAhmadiK. Hui Jiang AAML 42 6 0 30 May 2019
Securing Connected & Autonomous Vehicles: Challenges Posed by Adversarial Machine Learning and The Way Forward A. Qayyum Muhammad Usama Junaid Qadir Ala I. Al-Fuqaha AAML 94 191 0 29 May 2019
A backdoor attack against LSTM-based text classification systems Jiazhu Dai Chuanshuai Chen SILM 113 330 0 29 May 2019
Functional Adversarial Attacks Cassidy Laidlaw Soheil Feizi AAML 100 185 0 29 May 2019